In a manufacturing line of almost any type, there are a number of factors that control and/or affect the quality of the manufacturing process and of the product produced by the process. Some of the controlling or operative factors are numeric, such as temperature, time, distance between stations, tool settings, etc. These numeric factors are easily quantifiable. Other factors are non-numeric and are not readily quantifiable. Such factors, called "attribute" information, include the specific machine or tool, the particular operator or combination of operators, the work-shift, quality of starting materials, and the like. Each of the numeric and non-numeric factors controls or has an effect on the quality of the final product. For adequate control of the manufacturing line, it is desirable to optimize its parametrics (numeric information) as well as its attributes (non-numeric information).
It would be very useful to be able to quantify the non-numeric factors. By doing so, a line manager or supervisor could then make appropriate adjustments to the manufacturing line to obtain improved product yields or quality.
As an illustration of the problem, consider the manufacturing of an MLC (multi-layer ceramic) package. The manufacturing process consists of stacking many layers of ceramic "sheets". The stacked sheets are then sintered. The process involves multiple intermediate or starting products and materials, different tools, and multiple operators. The parametrics include the number of sheets in a stack, the number of stacks in the line, and the sintering temperature and times. The attributes of the MLC manufacturing process include such things as the identities of the operators (OP-ID), the particular stacking tool(s) used on the line, the particular sintering chamber(s), the particular measuring tools, the work-shift(s) (that is, whether the line is running on the day shift, the night shift or the "graveyard" shift), the vendors from whom starting materials are purchased, etc.
Process yield is the primary performance measure. It is desired to evaluate the performance of all the tools and operators used on the MLC manufacturing line so that "bad" tools can be fixed or replaced and "poor" operators can be retrained. The evaluating mechanism should itself yield good results even when not all the combinations of attributes occur in reality. In addition, the mechanism should resolve conflicting "opinions" correctly.
The present inventors are aware of a number of known systems which purport to control manufacturing processes. To their knowledge, all of the known systems operate on numeric data only. Such known systems are represented by the following issued U.S. patents:
______________________________________ U.S. Pat. No. 4,089,056 METHOD AND AUTOMATED EQUIPMENT FOR THE TRACK- ING, CONTROL AND SYNTHESIZ- ING OF MANUFACTURING PERFORMANCE FIGURES. U.S. Pat. No. 4,115,848 METHOD AND SYSTEM FOR CONTROLLING PLANTS. U.S. Pat. No. 4,328,556 CONTROL SYSTEM OF PLANTS BY MEANS OF ELECTRONIC COMPUTERS. U.S. Pat. No. 4,604,718 COMPUTER SIMULATION SYSTEM. U.S. Pat. No. 4,858,154 INTERLABORATORY QUALITY ASSURANCE PROGRAM. U.S. Pat. No. 4,870,590 MANUFACTURING LINE CONTROL SYSTEM. U.S. Pat. No. 5,008,842 METHOD OF SEQUENTIAL MONITORING AND APPARATUS FOR PRACTICING THE SAME. U.S. Pat. No. 5,047,947 METHOD OF MODELLING THE ASSEMBLY OF PRODUCTS TO INCREASE PRODUCTION YIELD. ______________________________________
The known systems exemplified by the above-listed patent disclosures all have at least one thing in common. None of them takes into account the non-numeric components of the manufacturing line process which contribute to the product yield of the line.
For example, the '056 patent describes a system for generating coded information from a plurality of electromechanical transducer units associated with respective machines to be supervised. Control of the manufacturing line is based on the data collected from the transducer units.
The '848 and '556 patents describe related process control systems and methods in which the operation of the plant (e.g., an electric power generating plant, a chemical processing plant, etc.) is controlled on the basis of tables stored in a computer and variations from norms detected by process input devices. The system is continuously controlled on the basis of comparing measured parameters with information stored in the tables.
The '718 patent describes a system for computer simulating the operation of a user-specified automated manufacturing and/or materials handling facility. The facility designer specifies various computer-controlled components and operating parameters which are to be tested. The designer selects from lists of predetermined components and operating parameters. The computer then creates an operational prototype model of the actual system.
The '154 patent describes a technique for statistically evaluating the performance, precision, and/or accuracy of one of a plurality of like instruments. The technique calls for comparing the performance of each instrument located in physically disparate locations. The patent is specifically directed to evaluating the performance of blood analyzers as part of an Interlaboratory Quality Assurance Program (IQAP).
The '590 patent describes a manufacturing line control system in which various analog, digital and status signal information issuing from a product on the line is evaluated. Control signals are then issued to the manufacturing line based on the detected product information.
The '842 patent describes a method and apparatus for sequentially monitoring the state of a working manufacturing line. As with other known systems, sensors on the line detect various parameters on the manufacturing line, including emulsion application, web density, web winding, etc. As with other known systems, all of the parameters measured are numeric quantities.
The '947 patent describes a method for increasing the production or manufacturing yield of a product by the application of mathematical modeling techniques on the statistical distributions of major components of the product to maximize the production yield of the products. Initially, the statistical characteristics of significant performance specifications of each of the major components of the product are established for each manufacturing lot of that component. The statistically probable performance of products assembled from different manufacturing lots is evaluated to assess the performance sensitivity of the assembled product to different combinations of the components from different manufacturing lots.
In order to maximize the yield from a given manufacturing line, it is desirable to account for non-numeric, as well as numeric, factors. It is well known empirically that non-numeric factors can play a significant role in product yield or quality. For example, studies have shown that automobiles manufactured on a Monday are statistically likely to have a higher percentage of defects than those coming off the assembly line on a Tuesday or Wednesday. No two milling machines are identical. Two assembly lines using two different milling machines will produce products that are not exactly identical. This concept carries over to all aspects of a manufacturing process. While absolute identity of finished products is not always essential, there are times, perhaps in some critical processes, when it is desirable to come as close as possible to absolute uniformity of finished product, whether from a single manufacturing line or from a plurality of similar lines.
The present invention was developed to take into account non-numeric factors which affect manufacturing lines. The present invention overcomes the deficiencies of known systems in this respect.